In this practical guide, you'll learn how to leverage the power of the command line for doing data science. By combining small, yet powerful, command-line tools, you can quickly obtain, scrub, explore, and model your data. Even if you're already comfortable processing data with R or Python, being able to integrate the command line into your existing workflow will make you a more efficient and productive data scientist.
Learn essential concepts and built-in commands of the nix command line
Get started with your own Data Science Toolbox on either Linux, Mac OS X, or Microsoft Windows
Use classic command-line tools such as grep, sed, and awk. Obtain data from websites, APIs, databases, and spreadsheets
Parallelize and distribute data-intensive pipelines to remote machines, including AWS EC2
Clean data in CSV, JSON, and XML/HTML formats using csvkit, and jq, and scrape
Apply dimensionality reduction, clustering, regression, and classification algorithms
Visualize data and results from the command line using gnuplot and ggplot
Turn Bash one-liners and existing Python and R code into reusable command-line tools
Über den Autor
Jeroen Janssens is a senior data scientist at YPlan in New York City. His specialties are in machine learning, anomaly detection, and data visualization. Jeroen is passionate about building open source tools for doing data science. He obtained a B.Sc. in Life Sciences and an M.Sc. in Artificial Intelligence, both cum laude from Maastricht University, the Netherlands. Jeroen completed his Ph.D. in Machine Learning at the Tilburg center for Cognition and Communication, Tilburg University. Outside of work, you may find him biking the Brooklyn Bridge, beatboxing, or eating stroopwafels.
This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.
To get you started—whether you’re on Windows, OS X, or Linux—author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.
Discover why the command line is an agile, scalable, and extensible technology. Even if you’re already comfortable processing data with, say, Python or R, you’ll greatly improve your data science workflow by also leveraging the power of the command line.
* Obtain data from websites, APIs, databases, and spreadsheets
* Perform scrub operations on plain text, CSV, HTML/XML, and JSON
* Explore data, compute descriptive statistics, and create visualizations
* Manage your data science workflow using Drake
* Create reusable tools from one-liners and existing Python or R code
* Parallelize and distribute data-intensive pipelines using GNU Parallel
* Model data with dimensionality reduction, clustering, regression, and classification algorithms